Knowledge Mining Based on Applications of The Methods and Technologies of Risks Prediction

This paper is concerned with the knowledge mining approach in application to complex transportation systems. The approach is based on implementing the author’s original mathematical models and supporting them with risk prediction software technologies. Compared to existing methods, the analytically calculated risks depend on the time of periodic control, monitoring, and recovery. Rational use allows the problem to go from data mining according to events to knowledge mining from transportation safety monitoring data and statistics. On the basis of the mined knowledge, proactive decisions may be found before the occurrence of critical events.